testdim {ade4} | R Documentation |
This functions allow to test for the number of axes in multivariate analysis. The procedure is only implemented for principal component analysis on correlation matrix. The procedure is based on the computation of the RV coefficient.
testdim(dudi, ...) ## S3 method for class 'pca': testdim(dudi, nrepet = 99, nbax = dudi$rank, alpha = 0.05, ...)
dudi |
a duality diagram (an object of class dudi ) |
nrepet |
the number of repetitions for the permutation procedure |
nbax |
the number of axes to be tested, by default all axes |
alpha |
the significance level |
... |
other arguments |
An object of the class krandtest
. It contains also:
nb |
The estimated number of axes to keep |
nb.cor |
The number of axes to keep estimated using a sequential Bonferroni procedure |
Stephane Dray dray@biomserv.univ-lyon1.fr
Dray, S. (2007) On the number of principal components: A test of dimensionality based on measurements of similarity between matrices. Computational Statistics and Data Analysis, in press.
tab <- data.frame(matrix(rnorm(200),20,10)) pca1 <- dudi.pca(tab,scannf=FALSE) test1 <- testdim(pca1) test1 test1$nb test1$nb.cor data(doubs) pca2 <- dudi.pca(doubs$mil,scannf=FALSE) test2 <- testdim(pca2) test2 test2$nb test2$nb.cor